Current Issue : April-June Volume : 2026 Issue Number : 2 Articles : 5 Articles
This study adapts Fourier ptychography (FP) for high-resolution imaging in machine vision settings. We replace multi-angle illumination hardware with a single fixed light source and controlled object translation to enable a sequence of slightly shifted low-resolution frames to produce the requisite frequency-domain diversity for FP. The concept is validated in simulation using an embedded pupil function recovery algorithm to reconstruct a high-resolution complex field, recovering both amplitude and phase. For conveyor-belt transport, we introduce a lightweight preprocessing pipeline—background estimation, difference-based foreground detection, and morphological refinement—that yields robust masks and cropped inputs suitable for FP updates. The reconstructed images exhibit sharper fine structures and enhanced contrast relative to native lens imagery, indicating effective pupil synthesis without multi-LED arrays. The approach preserves compatibility with standard industrial optics and conveyor-style acquisition while reducing hardware complexity. We also discuss practical operating considerations, including blur-free capture and synchronization strategies....
Machine vision systems are crucial in intelligent scenarios, but actual image acquisition is frequently compromised by the inadequate proficiency of photosensors in photoadaptation. Inspired by biological vision, neuromorphic synaptic phototransistors endowed with photoadaptive capabilities have emerged as a prospective strategy. However, most synaptic phototransistors only exhibit unidirectional positive photoresponses, whereas those capable of bidirectional photoresponses offer a greater possibility of accurately capturing images in complex lighting scenes. Herein, bidirectional photoadaptable organic heterojunction synapse phototransistors as sensing and processing units in systems are reported, which facilitate image contrast enhancement and improve image feature extraction under adverse lighting conditions. The bidirectional plasticity transformation of biomimetic neuromorphic synapses is mimicked. Specifically, n–n heterojunctions exhibit a unidirectional excitatory postsynaptic current, whereas n-p heterojunctions show a bidirectional response with a more prominent inhibitory postsynaptic current. Most interestingly, by integrating the device characteristics into convolutional neural networks and simultaneously optimizing algorithm architecture, the details and edges of low-contrast images are markedly enhanced, and the accuracy of image recognition is increased to 97.4% within ten cycles. This work serves as a novel idea for the development of high-performance neuromorphic visual systems, rendering them promising candidates for in-sensor computing applications....
This study addresses critical safety and productivity challenges faced by tower crane operators due to limited visibility during lifting operations. An intelligent crane-mounted visual system was implemented to enhance operator visibility, reduce communication faults, and improve overall crane performance in high-rise construction. The study followed a five-stage methodology: a literature review of visual and sensor technologies for collision prevention, site visits to identify visibility challenges, a comparative analysis of cranes with and without the vision system, and an impact assessment on safety and quality. The crane-mounted video system significantly improved efficiency, safety, and work quality, reducing cycle time, defined as the duration from hook pickup to placement, by 25%, with this reduction statistically significant at p < 0.001 using a two-paired t-test. Fewer near-miss incidents and lower idle times for workers and operators were observed, even when a less experienced operator operated the system. A cost–benefit assessment indicates that crane vision systems can generate annual economic benefits exceeding 240,000 NIS through accident prevention and time savings, based on the project context. This study’s contribution lies in providing a comprehensive, real-world evaluation of retrofitting older cranes with advanced vision technologies, demonstrating measurable impacts on safety, productivity, and economic outcomes....
Integrating multicolor perception with neuromorphic vision systems, capable of emulating the procedures of image detection, storage, and local processing, represents a significant advancement in artificial visual technologies. However, challenges related to data fusion, system complexity, and stability must be addressed to fully realize the potential of this technology. In this work, a low-dimensional/three-dimensional (LD/3D) halide perovskite heterostructure consisting of Ag/LD perovskitoid/3D CsFAMA/ITO is fabricated, demonstrating excellent stability for 2 months combined with the co-existence of two switching modes, namely volatile and non-volatile. The former mode is leveraged to construct the nodes of the reservoir computing architecture, where the fusion rate of the electrical and optical signals is examined to achieve maximum recognition accuracy of multicolor handwritten MNIST images (84%). An ultra-low power consumption of 400 fJ per synaptic weight change is also recorded during red light irradiation. By combining experiments with different top electrode materials and extensive Density Functional Theory calculations on metal atom diffusion and clustering in the materials of interest, key atomic scale processes are identified that underlie the switching behavior and lead to improved memory performance. The ability of the proposed device configuration to accurately carry out multimodal recognition tasks opens new possibilities for realizing biomimetic systems....
The potential of artificial intelligence (AI) in leadership is debated—while some question its ability to replace human leaders, others argue that AI can help inspire followers. In this study, we integrate studies on human‐AI interaction with the literatures on visionary leadership and social perception to examine the impact of outsourcing the creation and delivery of visions to AI. We propose that vision delivery by an AI avatar, compared to a human speaker, has a positive indirect effect on follower motivation through perceived leader competence but a negative indirect effect through perceived leader warmth. Moreover, we argue that these effects depend on followers' perceptions of who created the vision. Specifically, we propose that the positive indirect effect via perceived leader competence is stronger when followers believe the vision was created by AI rather than a human. Conversely, we argue that the negative indirect effect via perceived leader warmth is more strongly negative when followers believe a human leader outsourced the delivery of his or her vision to AI. We find support for our hypotheses in an experiment with 260 participants. Our research advances the understanding of both the benefits and drawbacks of outsourcing visionary leadership to AI....
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